Light microscopy chips and data analysis methodology for quantitative localzied surface plasmon resonance (LSPR) biosensing and imaging

ABSTRACT

A chip for localized surface plasmon resonance (LSPR) biosensing and imaging having a glass coverslip compatible for use in a standard microscope and at least one array of functionalized plasmonic nanostructures patterned onto the glass coverslip with electron beam nanolithography. The nanostructures can be regenerated allowing the chip to be used multiple times. Also disclosed is a method for determining the fractional occupancy values for surface-bound receptors as a function of time for LSPR biosensing from the spectroscopic response of the array and modeling the photon count in each spectrometer channel, allowing for a functional relationship to be determined between the acquired spectrum and the fractional occupancy of binding sites on the array. Additionally disclosed is a method for the spatiotemporal mapping of receptor-ligand binding kinetics in LSPR imaging using the chip and projecting a magnified image of the array to a CCD camera and monitoring the binding kinetics of the array.

PRIORITY CLAIM

This application is a divisional application of U.S. application Ser.No. 14/039,288 filed on Sep. 27, 2013 by Marc P. Raphael et al.,entitled “LIGHT MICROSCOPY AND DATA ANALYSIS METHODOLOGY FORQUANTITATIVE LOCALZIED SURFACE PLASMON RESONANCE (LSPR) BIOSENSING ANDIMAGING,” which claimed priority from U.S. Provisional Application No.61/706,911 filed on Sep. 28, 2012 by Marc P. Raphael et al., entitled“LIGHT MICROSCOPY AND DATA ANALYSIS METHODOLOGY FOR QUANTITATIVELOCALZIED SURFACE PLASMON RESONANCE (LSPR) BIOSENSING AND IMAGING” andU.S. Provisional Application No. 61/839,428 filed on Jun. 26, 2013 byMarc P. Raphael et al., entitled “SILICON BACKING RING AND MULTIPLEXINGAPPLICATIONS FOR LSPR IMAGING.” The entire contents of each of thesecited applications and all references cited throughout this applicationand each of these cited applications are incorporated herein byreference.

CROSS REFERENCE

Cross reference is made to copending application Ser. No. 14/039,326,filed Sep. 27, 2013, entitled “CALIBRATING SINGLE PLASMONICNANOSTRUCTURES FOR QUANTITATIVE BIOSENSING,” by Marc P. Raphael, et al.,the disclosure of which is incorporated herein by reference in itsentirety.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates to light microscopy-based chips andquantitative analysis methodology for localized surface plasmonresonance (LSPR) biosensing and imaging.

Description of the Prior Art

Localized surface plasmon resonance (LSPR) is an emerging technique inthe field of label-free biosensing which is currently dominated by theclosely related, but more mature surface plasmon resonance (SPR)technique. (P. Englebienne, Analyst, 123, 1599-1603 (1998); A. J. Haeset al., J. Am. Chem. Soc., 124, 10596-10604 (2002); N. Nath et al.,Anal. Chem., 74, 504-509 (2002); B. Sepulveda et al., Nano Today, 4,244-251 (2009); J. Zhao et al., Nanomedicine, 1, 219-228 (2006)). Bothemploy the coupling of light with metallic structures for the excitationof a plasmonic resonance and both take advantage of the fact that theresonance is sensitive to changes in the index of refraction near themetallic surface and thereby can be used to detect the presence ofanalytes such as proteins or nucleic acids. In SPR, total internallyreflected light, typically introduced by a prism, is incident at the“resonant” angle that excites surface plasmon polaritons propagatinglaterally along a planar, thin metal film. The sensitivity of theresonance to the presence of analytes extends hundreds of nanometersabove the thin film's surface. (L. S. Jung et al., Langmuir, 14,5636-5648 (1998) and K. Kurosawa et al., Phys. Rev. B, 33, 789-798(1986)). By contrast, the localized nature of the LSPR nanostructures,typically 50 to 150 nm in diameter, allows for a range of incident lightangles to be utilized, from normal to totalinternally reflected, and thesensitivity to analyte is confined to within tens of nanometers from thesurface. (M. D. Malinsky et al., J. Am. Chem. Soc., 123, 1471-1482(2001)).

Both techniques can be used for imaging, such that spatial and temporalinformation of analyte binding is acquired, although the concept of LSPRimaging offers some distinct advantages over that of SPR imaging. First,because the spatial resolution of LSPR is restricted only by the size ofthe nanoparticle, the imagery is in principle diffraction limited andindeed spectroscopic-based biosensing with single nanostructures hasalready been achieved. (K. M. Mayer et al., Nanotechnology, 21 (2010)and G. J. Nusz et al., Anal. Chem., 30, 984-989 (2008)). By contrast,traditional SPR configurations have a lateral spatial resolution that islimited by the decay length of the surface plasmon polaritons, which ison the order of microns for the gold thin films typically employed. (C.E. Berger et al., Anal. Chem., 70, 703-706 (1998) and B. Rothenhausleret al., Nature, 332, 615-617 (1988)). In addition, the fact that SPR issensitive to dielectric variations hundreds of nanometers above themetallic surface can result in a convolution of solution- andsurface-based changes. Finally, the ability to excite LSPR resonances ata range of incidence angles allows for the straightforward incorporationinto commercially available wide-field microscopes employing highnumerical apertures whereas SPR imaging configurations must be custombuilt.

In order to realize its promise and overtake the older SPR technology,methodologies for LSPR biosensing must be developed that allow forquantitative determination of important physical quantities such as thefractional occupancy of receptor sites at the surface. Ideally thesemeasurements would be made on a platform also capable of LSPR imaging sothat both spatial and temporal information could be gainedsimultaneously. The fractional occupancy of binding sites, f, is ofparticular interest because it can be used to calculate the analyteconcentration at the sensor surface if the reaction rate constants areknown or, conversely, to determine the rate constants if the analyteconcentration is known.

BRIEF SUMMARY OF THE INVENTION

The present invention provides a chip for localized surface plasmonresonance (LSPR) biosensing and imaging having a glass coverslipcompatible for use in a standard microscope and at least one array offunctionalized plasmonic nanostructures patterned onto the glasscoverslip with electron beam nanolithography. Also disclosed is a methodfor determining the fractional occupancy values for surface-boundreceptors as a function of time for LSPR biosensing and imaging usingthe chip and spectroscopically charactering the array, modeling thephoton count in each spectrometer channel, and functionally relating theacquired spectrum to a fractional occupancy of binding sites.Additionally disclosed is a method for the spatiotemporal mapping ofreceptor-ligand binding kinetics in LSPR imaging using the chip andprojecting a magnified image of the array to a CCD camera and monitoringthe binding kinetics of the array.

The purpose of the invention is to devise a light microscopy-basedinstrumental and quantitative analysis methodology for LSPR biosensingthat determines surface-receptor fractional occupancy, as well as anLSPR imaging technique for the spatio-temporal mapping of bindingevents. There is currently no alternative method for measuring thefractional occupancy of surface-bound receptors, with the space and timeresolution presented herein, on a commercially-available lightmicroscopy platform that is also compatible with fluorescence anddifferential interference contrast (DIC) microscopy.

This application of LSPR biosensing and imaging has several advantages:(1) measurements are made in real-time, (2) the nanostructures arelithographically patterned onto standard glass coverslips enabling moretraditional imaging techniques such as fluorescence and bright fieldimagery to be readily integrated, and (3) the nanostructures arecalibrated for the quantitative determination of concentration as afunction of time and space.

These and other features and advantages of the invention, as well as theinvention itself, will become better understood by reference to thefollowing detailed description, appended claims, and accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an illustration of the portion of the light train used for theexcitation of the biofunctionalized gold nanostructures as well as thesimultaneous detection of spectra and CCD imagery. P1 and P2 are crossedpolarizers, S is a 50/50 beam splitter and LS is the light source. Anillustration of a biofunctionalized gold nanostructure located atop theglass surface is shown as well in which the darker structures representthe receptors and the lighter structures represent the analytes.

FIG. 2 shows three 80 nm diameter nanostructures imaged in (a)brightfield and (b) with crossed polarizers at a microscopemagnification of 250×. The spacing between nanostructures was 1 μm. Themedium was DDW, and the images were contrast enhanced for clarity.

FIG. 3 shows SEM images of 20×20 arrays of varying pitch size: (a) 300nm, (b) 400 nm, and (c) 600 nm. The images were taken on a witnesssample in which the Cr under-layer was left in place for the sake ofpreventing charging problems in the SEM. All scale bars are 1 μm.

FIG. 4 shows SEM images of nanostructures of varying size and shape: (a)110×65 nm rectangles, (b) 80 nm discs, and (c) 130 nm discs. The imageswere taken on a witness sample in which the Cr under-layer was left inplace for the sake of preventing charging problems in the SEM. All scalebars are 100 nm.

FIG. 5 shows LSPR peaks of three arrays with pitches of 300 nm (highestpeak), 400 nm (shortest peak) and 600 nm (middle peak). All arraysconsisted of ellipsoidal-shaped nanostructures with base dimensions of70×75 nm. The spectra were taken in PBS, without flow.

FIG. 6 shows a drift study: 172 spectra recorded over the course of onehour. The inset shows the data at the peak with a scale bar of length(N)^(1/2), where N=20300, indicating the standard deviation from thecounting statistics inherent in the spectrometer. The spectra were takenwith PBS, flowing at a rate of 10 μL/min.

FIG. 7 shows spectra from five studies, each of which was proceeded byplasma ashing for the removal of all organics, followed by SAM layerdeposition and subsequent biofunctionalization with biotin. All studieswere conducted on the same array in PBS at a flow rate of 10 μL/min.FIG. 7(a) shows raw data, and FIG. 7(b) shows normalized data.

FIG. 8 shows LSPR spectra before (black) and after (gray) saturationwith 1 μM of neutravidin. The spectra were taken with PBS, flowing at arate of 10 μL/min.

FIG. 9 shows neutravidin specific binding studies at 1 μM, 250 nM and 50nM. The data were taken on the same array with the analyte in PBS,flowing at a rate of 10 μL/min. Between studies the array was subjectedto plasma ashing for the removal of all organics, followed by theredeposition of the SAM layer and subsequent biofunctionalization withNHS-biotin.

FIG. 10 shows specific (gray) vs. non-specific binding (black) for 250nM neutravidin. For the non-specific study, no biotin was conjugated tothe SAM layer. The data were taken on the same array in PBS, flowing ata rate of 10 μL/min.

FIG. 11 shows LSPR imaging data (gray) versus spectroscopic data (black)for the 250 nM neutravidin specific binding study. The data were takensimultaneously on the same array with the analyte in PBS, flowing at arate of 10 μL/min. The region of interest (ROI) intensity is the averageintensity of the pixels bounded by the gray box in the inset image. Thearray size was 8×8 μm.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides a methodology for the determination ofthe time-dependence of the surface-receptor fractional occupancy, f(t),based upon LSPR spectroscopic measurements using an array offunctionalized gold plasmonic nanostructures. The nanostructures werepatterned by electron-beam nanolithography (EBL) into 20×20 arrays andeach array as a whole characterized spectroscopically in a reflectedgeometry on an inverted light microscope. The data analysis methodologyof the present invention models the photon count in each spectrometerchannel as the sum of a baseline scattering rate and a scattering termsensitive to the small dielectric perturbations due to the binding ofbiomolecules at the surface of the nanostructures. This non-linear leastsquares approach to the data analysis sums over hundreds of thesechannels, at each point in time, giving it a distinct statisticaladvantage over a single channel approach, such as monitoring the peakwavelength. In this way, each acquired spectrum can be functionallyrelated to a fractional occupancy of binding sites, f(t). One embodimentof the invention is the ability to measure, for the first time withLSPR, the binding kinetics of f(t) with the biotin-neutravidin bindingpair and compare the obtained occupancy rates when varying theneutravidin concentration in solution from 50 nM to 1 μM. Anotherembodiment of the invention is a technique for regenerating the goldnanostructure arrays so that the same array of nanostructures can beused for repeated calibration and fractional occupancy measurements.This eliminates the uncertainties that can be introduced by thevariability in the fabrication process when comparing results fromdifferent arrays. It is also unique in that it allows for fractionaloccupancy measurements in experiments in which the array is notsaturated, provided it has been calibrated in a previous experiment orat the end of the current experiment. A further embodiment of theinvention is a technique for the spatio-temporal measurements of analytebinding, obtained by projecting the magnified image of the array on to acharge coupled device (CCD) camera. Binding kinetics can be followedwith a temporal resolution of 200 ms and a spatial resolution defined bythe area of the array which was 8 m². A unique feature of theseembodiments is that both the spectroscopic and the imaging applicationcan be performed simultaneously. Also unique is that the experimentstake place on a commercially-available inverted light microscope so thatthe techniques can be integrated with other more establishedlight-microscopy techniques such as fluorescence and differentialinterference contrast (DIC).

Description of Materials Used

Biosensing

SH—(CH₂)₁₁-EG₃-NH₂ (SPN) and SH—(CH₂)₈-EG₃-OH (SPO) were purchased fromProchimia (Poland). Anhydrous 200 proof ethanol was purchased fromSigma-Aldrich (Milwaukee, Wis.). NHS-biotin, neutravidin (NA) and 10 mMphosphate buffered saline consisting of 140 mM NaCl and 10 mM KCl, pH7.4 (PBS) were purchased from Thermo Scientific (Rockford, Ill.). No.1.5, 25.4 mm diameter borosilicate glass coverslips were purchased fromWarner Instruments (Hamden, Conn.). Ultrapure 18.2 MΩ deionizeddistilled water (DDW) was used as purified by a Milli-Q system fromMillipore Ltd.

Electron-Beam Lithography

The electron-beam (e-beam) resists used were polymethyl methacrylate 4%in anisole (PMMA A4) and 6% ethyl lactate methyl methacrylate copolymerin ethyl lactate (MMA EL6), both purchased from Microchem (Newton,Mass.). The chromium etchant CR-7 was purchased from Cyantek (Fremont,Calif.) which is a concentrated perchloric acid-based etchant consistingof 9% (NH₄)₂Ce(NO₃)₆)−6% HClO₄+H₂O. Methyl isobutyl ketone(MIBK)+isopropyl alcohol (IPA) in a 1:2 ratio were used for developingthe e-beam resists.

Nanostructure Array Fabrication

The substrates used for patterning the nanostructures were 25 mmdiameter glass coverslips with a nominal thickness of 170 μm. Typicalpretreatment of the substrates included soaking in piranha acid (3:1H₂SO₄: H₂O₂) for a minimum of 5 hours and then washing with copiousamounts of DDW. [Caution: piranha solution reacts violently with organicmaterials; it must be handled with extreme care, followed by rinsingwith copious amounts of DDW]. A 10 nm chromium thin film was depositedprior to spinning the e-beam resists in order to eliminate chargingduring patterning of the nanostructures and when imaging them afterlift-off. Substrates were then rinsed with acetone followed by IPA andbaked on a hot plate to dehydrate the surface and promote resistadhesion. A bilayer process was used to facilitate lift-off. In thisprocess, an undercut of the bottom layer was created to promotediscontinuity of the deposited metal film. The copolymer used, MMA-EL6,is closely related to PMMA and spins on with a thickness of 180 nm at2000 rpm. Next, PMMA A4 resist was spun at 3000 rpm to a thickness of250 nm. Samples were then patterned via EBL using area doses in therange of 200 to 400 μC/cm² and various beam deflection profiles in orderto adjust the size and shape of the nanostructures. The samples weredeveloped for 1 minute in a MIBK:IPA bath. The chromium layer waswet-etched from the bottom of the pattern using CR-7 etchant. A Ti/Aulayer was deposited using a Temescal electron-beam evaporator. Followingthe metal deposition, the PMMA/copolymer bilayer was lifted off bysoaking in acetone for 4 hours. After SEM inspection of the arrays, theremaining chromium was removed, leaving Au nanostructures atop a glasssubstrate.

The nanostructures were patterned in arrays of 20×20 structures witheach chip having 68 arrays. The pitch of the nanostructures within thearrays varied between 300 and 1000 nm and the size of the patternednanostructures varied from 50 to 150 nm. In addition, a number ofdifferent nanostructure shapes were investigated, including rectangles,squares, discs and ovals.

Nanostructure Functionalization and Characterization

Cleaning

Sample regeneration was obtained by plasma ashing in 300 mTorr of a 5%hydrogen, 95% argon mixture for 45 seconds in a 40 watt RF plasma(Technics Series 85 reactive ion etcher (RIE)). The efficacy of thisprocedure in removing thiols and other organics from the nanostructure'ssurface was confirmed by X-ray Photoelectron Spectroscopy (XPS) studieson 80 nm thick planar gold thin films used as proxies for thenanostructures. The thin films samples were functionalized and exposedto protein using protocols that were identical to those employed on thenanostructures. High resolution XPS scans (Thermo Scientific K-AlphaXPS) were taken of the sulfur S 2p peak and nitrogen N 1s peak centeredabout 400 eV and 162 eV respectively, using a pass energy of 20 eV froman Al Kα x-ray source focused to ˜400 μm spot size. After plasma ashing,no sulfur was detected and the nitrogen signal observed onprotein-coated samples was eliminated.

Biofunctionalization

Immediately following plasma ashing, the samples were incubated in 0.5mM of 3:1 SPN/SPO ethanolic solution for 18 hours in order to form aself-assembled monolayer (SAM) on the gold nanostructures. The sampleswere then rinsed with ethanol and dried with nitrogen gas. Forbiotinylation, 0.3 mM of NETS-biotin in PBS was drop coated on to thesample for reaction with the amine terminus of the SPN. After a two hourincubation, the sample was rinsed with DDW and dried with nitrogen gas.

LSPR Microscopy and Spectroscopy

CCD-based LSPR imaging as well as LSPR spectra were collected in areflected light geometry with an inverted microscope (Zeiss AxioObserver) using a 63×, 1.4 numerical aperture (NA) oil-immersionobjective and Koehler illumination. Imagery and spectra were obtainedsimultaneously by placing a beam splitter at the output port of themicroscope (see FIG. 1). The sample was epi-illuminated with polarizedlight from a 100 W halogen lamp and a crossed polarizer was used toreduce the background contribution from substrate-scattered light. Forthe spectral measurements, the focused image of the nanostructure arraywas projected on to the end of a 600 μm diameter optical fiber and thespectra were subsequently measured with a thermoelectrically-cooled,CCD-based spectrophotometer (Ocean Optics QE65000). The integration timewas 5 seconds per spectrum. For image acquisition, the focused image ofthe array was projected on to a thermoelectrically-cooled CCD camerawith 6.45 μm×6.45 μm sized pixels (Hamamatsu ORCA R²) with frameintegration times between 200 and 250 ms. Reference spectra wereconveniently obtained by a 20 μm translation of the stage to anarray-free spot on the sample. Dark spectra were obtained by shutteringthe light source.

FIG. 1 is an illustration of the portion of the light train used for theexcitation of the biofunctionalized gold nanostructures as well as thesimultaneous detection of spectra and CCD imagery. P1 and P2 are crossedpolarizers, S is a 50/50 beam splitter and LS is the light source. Anillustration of a biofunctionalized gold nanostructure located atop theglass surface is shown as well in which the darker structures representthe receptors and the lighter structures represent the analytes.

The epi-illumination setup used to produce highly contrasted images ofthe gold nanostructures utilized a combination of Koehler illuminationand crossed polarizers. First, the image of the Koehler illuminatorfield aperture was stopped down to a diameter of ˜30 μm so that only thearray of interest was illuminated, thus eliminating unwanted backgroundcontributions from the rest of the chip. Second, the condenser aperturewas stopped down so that effective numerical aperture (NA) ofillumination was less than 50% of the objective's total NA of 1.4. (Assuch, this configuration is the inverse of dark field illumination inthat dark field illuminates exclusively at high NA and collects at alower NA).

While these adjustments to the Koehler illuminator were adequate toobtain spectra there was still considerable background contribution dueto scattering from the substrate. To reduce this background, polarizedlight was used for illumination and a crossed-polarizer to filter thecollected light. The nanostructures are visible when usingcrossed-polarizers because of the dipole nature of their radiativeemission. While directly backscattered light from the nanostructures andsubstrate will have the same polarization as the incident light and isthus filtered by the crossed polarizer, off-axis dipole emission willcontain a component of the electric field which is perpendicular to theexcitation polarization.

For such an optical configuration, vector optics and Mie theory predictthat the magnified image of a single nanostructure will form two brightlobes and indeed this is what is observed. FIG. 2a is a bright fieldimage using unpolarized light of three nanostructures in DDW that are 80nm in diameter. When viewed with crossed polarizers, each individualspot is replaced by two spots (FIG. 2b ). The images were taken using a100× objective with an additional 2.5× optivar lens for a totalmagnification of 250× and contrast enhanced for clarity.

Analyte was introduced under continuous flow conditions using acustom-made microfluidic cell with the 10 μL/min flow rate controlled bya syringe pump. The flow cell volume was 36 μL. The microscope stage wasequipped with a temperature controlled insert and incubation chamberwhich kept the stage temperature and optical light train at 28.0±0.04°C. (PeCon GmbH). Under these conditions, the stage drift was less than 3nm/min.

Selecting the Optimal Array for Analyte Detection

EBL was used to pattern chips consisting of 68 arrays as describedabove. Each array consisted of 400 nanostructures in a 20×20arrangement. The size, shape and pitch of the nanostructures weresystematically varied from array to array in order to empiricallydetermine the geometry that best matched the optical configuration.Shapes included circular, square, rectangular and elliptical crosssections as shown in FIGS. 3 and 4. The dimensions along the crosssection were as small as 50 nm and as large as 150 nm; the height forall arrays was 80 nm. The pitch between nanostructures was varied from300 nm to 1 μm. The images shown in FIGS. 3 and 4 were taken on awitness sample in which the Cr under-layer was left in place for thesake of preventing charging problems in the SEM.

The selection criteria for the array best suited for LSPR imaging wasthat the location of the LSPR peak lie between 600 nm and 700 nm inorder to be well matched with the higher quantum efficiency (QE) rangeof the CCD camera. (For the wavelengths 650 nm, 750 nm, and 850 nm theQE of the camera was approximately 60%, 40%, and 20%, respectively.) Itwas found that nanostructures with approximate diameters or widths of70±10 nm met this criteria while also having large enough scatteringcross sections to allow for highly contrasted images to be obtained withcamera exposure times of 250 ms or less.

After down-selecting for arrays based on the LSPR peak wavelength, theline widths of each array were compared by measuring the full width athalf maximum as a function of pitch. In two-dimensional arrays ofnanostructures, radiative coupling and interference of the scatteredlight can vary both the position of the resonance peak and its width.FIG. 5 compares the LSPR peak of three arrays containing ellipsoidalnanostructures with 70×75 nm bases but varying in pitch from 300 nm to600 nm. The spectra were taken in PBS, without flow. The direction ofincident light polarization was parallel to the minor axis of theellipses. The reflectance was calculated as

${reflectance} = \frac{{N_{array}(\lambda)} - {N_{dark}(\lambda)}}{{N_{ref}(\lambda)} - {N_{dark}(\lambda)}}$where N_(array), N_(dark) and N_(ref) are the spectrometer counts forthe array, dark, and reference spectra, respectively. The 300 nm pitcharray showed a marked sharpening in the line width and was slightlyshifted relative to the 400 and 600 nm pitched arrays. As a result, the300 nm pitch array was used for all subsequent spectral- and image-basedbiosensing measurements.

The data analysis methodology introduced below requires as input thenumber of counts in each of the spectrometer's data channels. A slowlyvarying, homogeneous drift across the entire spectrum is accounted forin the model but if the drift has a chromatic dependence, then the modelcan falsely associate it with the binding of analyte at the surface. Athigh optical magnifications, the most common causes of such variationsare lateral stage drift, focus drift, and microfluidic-basedperturbations. FIG. 6 shows a drift study in which 172 spectra wereacquired over one hour. The spectra were taken with PBS, flowing at arate of 10 μL/min. The inset allows for the visualization of the spreadin the spectra by showing the data at the peak. The spread in counts atthe peak is comparable to the square root of the number of counts (asindicated by the scale bar), demonstrating that for the setup the countuncertainty in a given channel is dominated by the counting statisticsof the detector. The stability of the setup as demonstrated in FIG. 6enabled the quantitative data analysis approach described below.

FIG. 7 shows that the spectra measured on a given array are reliablyreproduced after repeated regenerations by plasma ashing, followed bybiofunctionalization. If the plasma ashing had damaged thenanostructures, thus varying their size or shape, or the subsequentbiofunctionalization steps were not reproducible, a variation in theLSPR peak position and width would be expected since both are known tobe highly sensitive to such effects. FIG. 7 plots the spectra from fivestudies, taken on the same array in PBS at a flow rate of 10 μL/min,each of which was proceeded by plasma ashing for the removal of allorganics, followed by SAM layer deposition and subsequentbiofunctionalization with NHS-biotin as described in the Materials andMethods section. FIG. 7a shows the raw data in which intensityvariations between studies are present. However, when normalized (FIG.7b ) the spectra are well reproduced. The differences between spectra inthe raw data are likely due to day-to-day variations in the illuminationintensity as well as slight differences in alignment when the chip ismounted on to the microscope. As will be shown below, thereproducibility displayed in FIG. 7b is necessary for the calibration ofa given array to be reliably applied to subsequent data runs on the samearray following the regeneration and biofunctionalization steps.

Data Analysis

To obtain the time-dependent fractional occupancy of receptors, f(t), wehave taken a non-linear least squares approach to the data analysis. Themean photon count per spectrometer channel, acquired over the detector'sintegration time (τ), can be expressed asN _(i)(t,t+τ)=A _(i)·∫_(t) ^(t+τ) dt′Γ _(i)(t′)  (1)where N _(i), A_(i) and Γ_(i) are the mean photon count, the incidentphoton flux and the photon scattering rate, respectively. The photonscattering rate can be approximated by the sum of an initial scatteringrate, Γ_(0,j), a term sensitive to the dielectric perturbation of thebio-molecules, Γ_(ϵ,i), and a time-varying background term, Γ_(B,i).Finite element simulations as well as dipole approximation modelingpredict a linear dependence of the photon scattering rate to thefractional occupancy, Γ_(ϵ,i)∝f, in which case the scattering rate canbe written asΓ_(i)(t)=Γ_(0,i)+Γ_(ϵ,i)+Γ_(B,i)=Γ_(0,i)+α_(i) ·f(t)+β_(i) ·g(t)  (2)where the background contribution is also assumed linear with respect toa separate function, g(t). Inserting these results into Eq. (1) yieldsN _(i)(t,t+τ)=γ_(i) τ+a _(i) f(t)·τ+b _(i) g(t)·τ  (3)where γ_(i)=A_(i)Γ_(0,i), a_(i)=A_(i)α_(i) and b_(i)=A_(i)β_(i). Thecalibration data used to determine the values of the coefficients γ_(i)and b_(i) were obtained with no analyte present (f=0) while thecalibration data for the determination of a_(i) were obtained after thesensor had been saturated with neutravidin (f=1). Once obtained, thesecoefficients were applicable to all the specific and non-specificbinding studies measured with the same array of nanostructures. Anexample of an f=0 spectrum versus an f=1 spectrum is shown in FIG. 6 inwhich the spectra were taken in PBS, flowing at a rate of 10 μL/min. Wenote that local topological features of the nanostructures such asdefects, edges and surface roughness will create a complex dependencebetween the observed signal and the actual fractional occupancy at thenanoscale. For this reason, there was no attempt to measure and modelindividual nanostructures or even tens of nanostructures. Insteadmeasurements were made on an ensemble of 400 nanostructures so thatthese local complexities are averaged out.

With the model thus established, the most probable values of f(t) arecalculated using our non-linear least squares formalism in which thefollowing log-likelihood function is minimized with respect to f

$\begin{matrix}{{\log_{e}\left\lbrack {P\left( {\left. \overset{r}{N} \middle| {f(t)} \right.,{g(t)},\tau} \right)} \right\rbrack} = {{{const}.{- \frac{1}{2}}}{\sum\limits_{i = 1}^{M}\frac{\left( {N_{i} - {\overset{\_}{N}}_{i}} \right)^{2}}{\sigma_{i}^{2}}}}} & (4)\end{matrix}$where N_(i) are the counts acquired in i^(th) channel of a spectrometerwith M total channels. As demonstrated in FIG. 6, the uncertainty in thenumber of counts in channel i is dominated by counting statistics, sothat σ_(i) ²=N. The error bars for the calculated f values aredetermined from the Gaussian co-variance matrix.Spectroscopic and Imaging Based Kinetic Measurements

In three separate experiments, neutravidin was introduced into the flowcell in concentrations of 1 μM, 250 nM and 50 nM. The time-dependentevolution of f for each concentration is shown in FIG. 9. The data weretaken on the same array with the analyte in PBS, flowing at a rate of 10μL/min. Between studies the array was subjected to plasma ashing for theremoval of all organics, followed by the redeposition of the SAM layerand subsequent biofunctionalization with NHS-biotin.

In FIG. 9, f=1 was determined independently for each neutravidinconcentration by assuming saturation at the end of the transitionalthough a slight positive slope was measurable. To determine whetherthis slope was due to specific or non-specific binding, control studieswere conducted in which the same experiments were repeated on the samearray but without biotin conjugated to the SAM layer. As shown in FIG. 8for the 250 nM neutravidin case, the slope at the end of the specificbinding run is largely accounted for by non-specific binding and thushelps validate the f=1 assumption.

The co-plot in FIG. 10 is possible because the calibration constantsobtained from a previous saturation study, namely the 1 μM neutravidinstudy, were used in the analysis of the 250 nM non-specific bindingdata. The reliability of this procedure is dependent upon thespectroscopic features and sensitivity of the resonance peak beingrepeatable from one experiment to the next; a criterion achieved byregenerating and reusing the same array of nanostructures for allexperiments (see FIG. 7b ).

We now turn from the analysis of the spectroscopic data to the kineticsas measured simultaneously with the CCD camera. FIG. 11 plots the timecourse for the 250 nM neutravidin specific binding study as measured bythe LSPR imaging technique and, for the sake of comparison, co-plots theanalyzed spectroscopic data. Each LSPR imaging datum point is theaverage of the CCD pixel values contained within a region of interest(ROI) which incorporates the array of nanostructures (see FIG. 11inset). As shown in FIG. 8, the binding of proteins to the surface ofthe gold nanostructures not only results in a shift of the resonancepeak position but also in an increase in the scattering rate for thewavelengths between 610 nm and 750 nm. As a result, the image of thenanostructures brightens with increased fractional occupancy. FIG. 11demonstrates that the LSPR imaging technique presented here has thesensitivity to monitor binding kinetics at the surface of the goldnanostructures for a 20×20 array. The time resolution has been enhancedfrom the 5 seconds spectrometer exposure time to 200 ms for the CCDcamera exposure time as a result of the fact that the CCD pixel count isa sum over all the LSPR peak wavelengths, with each wavelength weightedby QE(λ) of the detector. Another important advantage of LSPR imaging isthat it gives spatial information as well as temporal. The current studyis restricted to a ROI that incorporates the entire array, an area of 8μm².

The above descriptions are those of the preferred embodiments of theinvention. Various modifications and variations are possible in light ofthe above teachings without departing from the spirit and broaderaspects of the invention. It is therefore to be understood that theclaimed invention may be practiced otherwise than as specificallydescribed. Any references to claim elements in the singular, forexample, using the articles “a,” “an,” “the,” or “said,” is not to beconstrued as limiting the element to the singular.

What is claimed as new and desired to be protected by Letters Patent ofthe United States is:
 1. A method for determining fractional occupancyvalues for surface-bound receptors as a function of time for localizedsurface plasmon resonance (LSPR) biosensing and imaging, comprising:using a chip for LSPR biosensing, comprising a glass coverslipcompatible for use in a standard microscope, wherein at least one arrayof functionalized plasmonic nanostructures for LSPR biosensing andimaging has been patterned onto the glass coverslip with electron beamnanolithography, wherein the functionalized plasmonic nanostructures arecalibrated for a quantitative determination of concentration as afunction of time and space; projecting a focused image of the array tospectroscopically characterize the array; modeling the photon count ineach spectrometer channel as the sum of a baseline scattering rate and ascattering term sensitive to small dielectric perturbations, wherein themodeling can sum hundreds of spectrometer channels at each point intime; and functionally relating an acquired spectrum to a fractionaloccupancy of binding sites using a non-linear least squares calculation.2. The method of claim 1, wherein the functionalized plasmonicnanostructures comprise functionalized gold plasmonic nanostructures. 3.The method of claim 1, wherein the array comprises 20×20 nanostructures.4. The method of claim 1, wherein the pitch between the arrays is in therange from 150 to 1000 nm.
 5. The method of claim 1, wherein the size ofthe patterned nanostructures is in the range from 50 to 150 nm.
 6. Themethod of claim 1, wherein the shape of the nanostructures comprisesrectangles, squares, discs, ovals, or any combination thereof.
 7. Themethod of claim 1, wherein the nanostructure arrays can be regenerated.8. The method of claim 7, wherein the nanostructure arrays areregenerated by plasma ashing.